Profluent unveils Protein2PAM AI model to design CRISPR systems targeting more of human genome, CEO Ali Madani announces. Tool predicts PAM sequences for expanded gene editing.

Depth degradation is a problem biologists know all too well: The deeper you look into a sample, the fuzzier the image becomes. A worm embryo or a piece of tissue may only be tens of microns thick, but the bending of light causes microscopy images to lose their sharpness as the instruments peer beyond the top layer.
To deal with this problem, microscopists add technology to existing microscopes to cancel out these distortions. But this technique, called adaptive optics, requires time, money, and expertise, making it available to relatively few biology labs.
Now, researchers at HHMI’s Janelia Research Campus and collaborators have developed a way to make a similar correction, but without using adaptive optics, adding additional hardware, or taking more images. A team from the Shroff Lab has developed a new AI method that produces sharp microscopy images throughout a thick biological sample.
Researchers at Duke University have uncovered the molecular inner workings of a material that could underpin next-generation rechargeable batteries.
Unlike today’s popular lithium-ion batteries that feature a liquid interior, the lithium-based compound is a solid at operational temperatures. But despite its rigid interior structure, charged ions are still able to quickly travel through, making it a “super ionic” material. While researchers have been interested in this compound for some time, they have not known how lithium ions are able to pass through its solid crystalline structure so easily.
The new results answer many standing questions, showing surprising liquid-like behavior at the atomic level. With these insights in hand, as well as the machine learning models used to obtain them, researchers are set to explore similar recipes to solve many of the field’s long-standing challenges.
A breakthrough in artificial intelligence.
Artificial Intelligence (AI) is a branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence. These tasks include understanding natural language, recognizing patterns, solving problems, and learning from experience. AI technologies use algorithms and massive amounts of data to train models that can make decisions, automate processes, and improve over time through machine learning. The applications of AI are diverse, impacting fields such as healthcare, finance, automotive, and entertainment, fundamentally changing the way we interact with technology.
Diverse Applications Beyond Elderly Care
While companion robots have traditionally been used to support the elderly, their utility is expanding to other demographics prone to loneliness, such as office workers and university students. Dr. Li’s research in China reveals that these groups often experience social isolation and lack the resources for meaningful companionship. The physical presence of robots like Moflin and LOVOT, which offer tactile interactions, differentiates them from virtual assistants and enhances their effectiveness in providing emotional support.
[Read More: Can AI Step Out from Virtual to Real Companionship?].
Summary: Researchers have developed a Genetic Progression Score (GPS) using artificial intelligence to predict the progression of autoimmune diseases from preclinical symptoms to full disease. The GPS model integrates genetic data and electronic health records to provide personalized risk scores, improving prediction accuracy by 25% to 1,000% over existing models.
This method identifies individuals at higher risk earlier, enabling timely interventions and better disease management. The framework could also be adapted to study other underrepresented diseases, offering a breakthrough in personalized medicine and health equity.